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  • 1.
    Ahmadi, Alireza
    et al.
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Block, Jan
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Garmabaki, Amir
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Project: Efficient Performance Based Air Vehicle Maintenance, Supported by VINNOVA (NFFP-6), Luleå University of Technology, Saab Support and Services, SAAB Aeronautics2014Annet (Annet (populærvitenskap, debatt, mm))
  • 2.
    Ahmadi, Alireza
    et al.
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Block, Jan
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Garmabaki, Amir
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Project: Enhanced Life Cycle Assessment for Performance-Based Logistics, Supported by Vinnova (NFFP-5), Saab Support Service and Luleå University of Technology2014Annet (Annet (populærvitenskap, debatt, mm))
  • 3.
    Ahmadi, Alireza
    et al.
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Garmabaki, Amir
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Ghodrati, Behzad
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Kumar, Uday
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Optimum inspection interval for hidden functions during extended life2015Inngår i: International Journal of COMADEM, ISSN 1363-7681, Vol. 18, nr 3, s. 45-49Artikkel i tidsskrift (Fagfellevurdert)
  • 4.
    Ahmadi, Alireza
    et al.
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Ghodrati, Behzad
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Garmabaki, Amir Soleimani
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Kumar, Uday
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Optimum inspection interval for hidden functions during extended life2014Konferansepaper (Fagfellevurdert)
  • 5.
    Ahmadi, Mahdieh
    et al.
    Department of Industrial Engineering, Mazandaran University of Science and Technology, Babol.
    Mahdavi, Iraj
    Department of Industrial Engineering, Mazandaran University of Science and Technology, Babol.
    Garmabaki, Amir
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Multi up-gradation Software Reliability for Open Source Software2016Inngår i: Current Trends in Reliability, Availability, Maintainability and Safety: An Industry Perspective / [ed] Uday Kumar; Alireza Ahmadi; Ajit Kumar Verma; Prabhakar Varde, Encyclopedia of Global Archaeology/Springer Verlag, 2016, s. 691-702Konferansepaper (Fagfellevurdert)
    Abstract [en]

    Nowadays, software companies have to continuously do up-gradation or add-ons in their software to survive in the market. This paper presents an effective reliability model for multi release open source software (OSS), which derived based on software lifecycle development process (SDLC) proposed by Jørgensen [1]. Most of OSS reliability models proposed in the literature are based on closed-form methodology and do not consider the properties of OSS in the model structure. The proposed model, incorporate bugs removed from two different phases, namely a pre-commit test and parallel debugging test. Furthermore, the proposed model is based on the assumptions that the overall fault removal of the new release depends on the reported faults from the previous release of the software and on the faults generated due to adding some new functionalities to the existing software system. The parameters of model have been estimated on real software failure dataset with three releases and goodness of fit of values have been calculated. Results show that the proposed model fits the data reasonably well and present better accuracy in comparison with other methods.

  • 6.
    Ahmadi, Mahdieh
    et al.
    Department of Industrial Engineering, Mazandaran University of Science and Technology, Babol.
    Seneviratne, Dammika
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Garmabaki, Amir
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    An approach to Symbolic Modelling: a Railway Case study for Maintenance Recovery Level Identification2017Inngår i: Proceedings of MPMM 2016: 6th International Conference on Maintenance Performance Measurement and Management, 28 November 2016, Luleå, Sweden / [ed] Diego Galar, Dammika Seneviratne, Luleå: Luleå tekniska universitet, 2017, s. 187-Konferansepaper (Fagfellevurdert)
    Abstract [en]

    Increasing demand for quality and reliability of the asset is progressively seen as a motivation for improved maintenance procedure and management. Always the role of qualitative maintenance data is neglected in the maintenance recovery level identification. Human factor parameter in the maintenance and qualitative technical data, for instance, maintenance experience, maintenance knowledge, training, quality before maintenance, number of previous maintenance, maintenance documentation and environmental condition can be collected and evaluated to increase the accuracy of maintenance recovery estimation. This information always expressed linguistically and considering their effect in the recovery model is challenging. The aim of this study is to propose a symbolic model to capture the effect of above qualitative factor on maintenance recovery level. Fuzzy inference systems are applied to qualitative expert knowledge to extract the percentage effect which can be incorporated in the recovery level model. The tamping railway case study is considered to validate the model. The results show that the maintenance experience and environmental condition are playing main role in maintenance quality. The application of above method can be extended to asset condition assessment in combination with data driven and physical model

  • 7.
    Aliyari, Mostafa
    et al.
    Politecnico di Milano.
    Barabadi, Abbas
    UiT The Arctic University of Norway.
    Barababadi, R.
    Amir Kabir College, Jajarm.
    Garmabaki, Amir
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Failure and repair data analysis of power distribution systems: a case study2017Inngår i: Risk, Reliability and Safety: Innovating Theory and Practice - Proceedings of the 26th European Safety and Reliability Conference, ESREL 2016 / [ed] Walls L.,Revie M.,Bedford T, London: CRC Press, 2017, s. 2046-2053Konferansepaper (Fagfellevurdert)
    Abstract [en]

    The basic function of electricity distribution system is to supply electrical energy as economically as possible to customer in different geographic with an accept-able level of reliability and quality [1]. The quality of electricity means the supplied current and voltage waveforms are essentially pure sinusoidal waveforms. By incorporating reliability and maintainability con-siderations in the system design and in the planning of system expansion, operation and maintenance the both quality and safety can be improved [2]. To obtain useful results from system reliability assessments, accurate values of component reliability parameters need to be estimated. If the outage database are collected properly, they can reflecting the conditions in which a component works. Hence, collecting, extraction and exploitation useful information from historical data getting more and more importance. A statistical significance of an outage database depends on the quality and reliability as well as number of records data in the database. Such database would describe the real conditions of network equipment more accurately. This study will exploit unplanned outages in electrical components of low voltage (LV) distribution systems in North Khorasan Electricity Distribution Company (NKEDC). The database containing 64035 outages and 150569 Kwh undistributed energy and total time of 2637430 minutes of outages in LV components from July 2010 to February 2016. Here, the main aim of the analysis is to identify the “Significant Few” failures as well as the current maintainability performance of each identified failure models in the power distribution. Such analysis will give a picture of current situation of the system. To start the analysis two meeting have been conducted with the expertise of company to identified the main failure model in the system. Thereafter, the collect data have been explored. The collected data are very detailed regarding the repair time. However, the recorded failure model and preliminary failure cause are not well collected in database. Moreover, we noticed that cause of the failure are not recorded using appropriate coding system that make extracting the data very difficult. Hence, at the first step appropriate coding system have been developed. In this stage, the required recommendation for improving the data collection have been provide and discussed with the company. Based on failure mechanism, of equipment and expert opinions 23 failure mode have been identified and then maintainability for these identified failure mode have been calculated. The trend test and the serial correlation test should all collected repair data are iid distributed and lognormal distribution is suitable tools to model the most identified failure modes

  • 8.
    Anand, Adarsh
    et al.
    Department of Operational Research, University of Delhi.
    Agarwal, Mohini
    University of Delhi.
    Bansal, Gunjan
    Department of Operational Research, University of Delhi.
    Garmabaki, Amir
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Studying product diffusion based on market coverage2016Inngår i: Journal of Marketing Analytics, ISSN 2050-3326, Vol. 4, nr 4, s. 135-146, artikkel-id 5Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Market coverage is an important attribute for determining the success of a product. The larger the market covered by a product is, the higher the amount of sales for that product will be. Market coverage strategies thus contribute to the success of a product in tapping the market. In this study, we emphasize the impact of market coverage on the rate of adoption in determining product sales. New product diffusion models based on the market covered are proposed. A methodological approach of weighted criteria is implemented to evaluate and rank the proposed models. The analysis is conducted on real-life sales datasets

  • 9.
    Barabadi, Abbas
    et al.
    University of Tromsø - The Arctic University of Norway.
    Garmabaki, Amir
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik. Islamic Azad University.
    Fuqing, Yuan
    Tromsø University.
    Lu, J.
    University of Tromsø - The Arctic University of Norway.
    Maintainability analysis of equipment using point process models2015Inngår i: 2015 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM): Singapore, 6-9 Dec. 2015, Piscataway, NJ: IEEE Communications Society, 2015, s. 797-801, artikkel-id 7385757Konferansepaper (Fagfellevurdert)
    Abstract [en]

    The maintenance cost can be reduced significantly by applying the maintainability principle in the design and operation phase. An effective maintainability prediction can help the designer to improve performance and safety of equipment. The analysis of historical repair by an affective statistical approach provides essential information for decision-making regarding the planning of operation and maintenance activities of the plant. However, the literature on field repair data is quite scarce and they are not detailed. This paper will try to provide step by step guideline for field repair data using point process models by a case study.

  • 10.
    Barabadi, Abbas
    et al.
    Tromsø University, Department of Engineering and Safety, UiT The Arctic University of Norway, Tromsø.
    Garmabaki, Amir
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Zaki, Rezgar
    Department of Engineering and Safety, UiT The Arctic University of Norway, Tromsø.
    Designing for performability: An icing risk index for Arctic Offshore2016Inngår i: Cold Regions Science and Technology, ISSN 0165-232X, E-ISSN 1872-7441, Vol. 124, s. 77-86Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Ice accretion affects the performability of offshore production facilities in various ways, including repair time and failure rate. It can increase power losses, life cycle costs and safety hazards. There are few studies and limited systematically collected information about the impact of ice accretion on performability and its attributes (reliability, maintainability, quality, safety and sustainability) for Arctic offshore production facilities. This paper will discuss the effects of different types of ice accretion on the performability of Arctic offshore production facilities. Then, to quantify their effect on the performability of offshore production facilities, an icing risk index is developed; its application is then shown by means of a case study.

  • 11.
    Calle Cordón, Álvaro
    et al.
    CEMOSA, Spain.
    Jiménez-Redondo, Noemi
    CEMOSA, Spain.
    Morales-Gámiz, J.
    CEMOSA, Spain.
    García-Villena, F. A.
    CEMOSA, Spain.
    Peralta-Escalante, J.
    CEMOSA, Spain.
    Garmabaki, Amir
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Famurewa, Stephen Mayowa
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Duarte, Emanuel
    Infraestruturas de Portugal, Lisbon, Portugal.
    Morgado, João
    Infraestruturas de Portugal, Lisbon, Portugal.
    Combined RAMS and LCC analysis in railway and road transport infrastructures2018Inngår i: Proceedings of 7th Transport Research Arena TRA, Vienna, Austria, 2018Konferansepaper (Fagfellevurdert)
    Abstract [en]

    Life-cycle cost (LCC) analysis is an assessment technique used to evaluate costs incurred during the life-cycle of a system to help in long term decision making. In railway and road transport infrastructures, costs are subject to numerous uncertainties associated to the operation and maintenance phase. By integrating in the LCC the stochastic nature of failure using Reliability, Maintainability, Availability and Safety (RAMS) analyses, maintenance costs can be more reliably estimated. This paper presents an innovative approach for a combined RAMS&LCC methodology for linear transport infrastructures which has been developed under the H2020 project INFRALERT. Results of the application of such methodology in two real use cases are shown, one for rail and another one for road. The use cases show how the approach is implemented in practice.

  • 12.
    Calle-Cordón, Álvaro
    et al.
    CEMOSA.
    Jiménez-Redondo, Noemi
    CEMOSA.
    Morales-Gámiz, F. J.
    CEMOSA.
    García-Villena, F.A.
    CEMOSA.
    Garmabaki, Amir
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Odelius, Johan
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Integration of RAMS in LCC analysis for linear transportinfrastructures: A case study for railways2017Inngår i: IOP Conference Series: Materials Science and Engineering, ISSN 1757-8981, E-ISSN 1757-899X, Vol. 236Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Life-cycle cost (LCC) analysis is an economic technique used to assess the totalcosts associated with the lifetime of a system in order to support decision making in long termstrategic planning. For complex systems, such as railway and road infrastructures, the cost ofmaintenance plays an important role in the LCC analysis. Costs associated with maintenanceinterventions can be more reliably estimated by integrating the probabilistic nature of thefailures associated to these interventions in the LCC models. Reliability, Maintainability,Availability and Safety (RAMS) parameters describe the maintenance needs of an asset in aquantitative way by using probabilistic information extracted from registered maintenanceactivities. Therefore, the integration of RAMS in the LCC analysis allows obtaining reliablepredictions of system maintenance costs and the dependencies of these costs with specific costdrivers through sensitivity analyses. This paper presents an innovative approach for acombined RAMS & LCC methodology for railway and road transport infrastructures beingdeveloped under the on-going H2020 project INFRALERT. Such RAMS & LCC analysisprovides relevant probabilistic information to be used for condition and risk-based planning ofmaintenance activities as well as for decision support in long term strategic investmentplanning.

  • 13.
    Esmaeili Kelishomi, A.
    et al.
    Xi'an Jiaotong University, Xi'an, China.
    Garmabaki, Amir Soleimani
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Bahaghighat, M.
    Raja University, Qazvin, Iran.
    Dong, J.
    Xi'an Jiaotong University, Xi'an, China.
    Mobile User Indoor-Outdoor Detection Through Physical Daily Activities2019Inngår i: Sensors, ISSN 1424-8220, E-ISSN 1424-8220, nr 3, artikkel-id 511Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    An automatic, fast, and accurate switching method between Global Positioning System and indoor positioning systems is crucial to achieve current user positioning, which is essential information for a variety of services installed on smart devices, e.g., location-based services (LBS), healthcare monitoring components, and seamless indoor/outdoor navigation and localization (SNAL). In this study, we proposed an approach to accurately detect the indoor/outdoor environment according to six different daily activities of users including walk, skip, jog, stay, climbing stairs up and down. We select a number of features for each activity and then apply ensemble learning methods such as Random Forest, and AdaBoost to classify the environment types. Extensive model evaluations and feature analysis indicate that the system can achieve a high detection rate with good adaptation for environment recognition. Empirical evaluation of the proposed method has been verified on the HASC-2016 public dataset, and results show 99% accuracy to detect environment types. The proposed method relies only on the daily life activities data and does not need any external facilities such as the signal cell tower or Wi-Fi access points. This implies the applicability of the proposed method for the upper layer applications.

  • 14.
    Fuqing, Yuan
    et al.
    Tromsø University.
    Barabadi, Abbas
    Tromsø University.
    Lu, J.M.
    Department of Engineering and Safety, UiT The Arctic University of Norway, Tromsø.
    Garmabaki, Amir
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik. Islamic Azad University.
    Performance Evaluation for Maximum Likelihood and Moment Parameter Estimation Methods on Classical Two Weibull Distribution2015Inngår i: 2015 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM): Singapore, 6-9 Dec. 2015, Piscataway, NJ: IEEE Communications Society, 2015, s. 802-806, artikkel-id 7385758Konferansepaper (Fagfellevurdert)
    Abstract [en]

    The two-parameter Weibull distribution is the most widely used distribution in reliability engineering. Parameter estimation is a key issue to apply the Weibull to practical engineering. This paper aims to compare the performance of the maximum parameter estimation method (MLE) and the moment parameter method. It firstly investigates some mathematical properties such as solution uniqueness, estimator's equivariance and the confidence interval, that are important to practice. Later on their performances have been evaluated by using simulation. In the simulation, data sets ranged from extreme small to large have been considered. Weibull distribution with increasing, constant and deceasing failure rate have been chosen in the simulation to ensure the simulation's results concrete.

  • 15.
    Garmabaki, Amir
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Project: Design of Fuzzy Programming Software2013Annet (Annet (populærvitenskap, debatt, mm))
  • 16.
    Garmabaki, Amir
    et al.
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Ahmadi, Alireza
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Ahmadi, Mahdieh
    Department of Industrial Engineering, Mazandaran University of Science and Technology, Babol.
    Maintenance Optimization Using Multi-Attribute Utility Theory2016Inngår i: Current Trends in Reliability, Availability, Maintainability and Safety: An Industry Perspective / [ed] Uday Kumar; Alireza Ahmadi; Ajit Kumar Verma; Prabhakar Varde, Encyclopedia of Global Archaeology/Springer Verlag, 2016, s. 13-25Konferansepaper (Fagfellevurdert)
    Abstract [en]

    Several factors such as reliability, availability, and cost may consider in the maintenance modeling. In order to develop an optimal inspection program, it is necessary to consider the simultaneous effect of above factor in the model structure. In addition, for finding the optimal maintenance interval it is necessary to make trade-offs between several factors, which may conflicting each other as well. The study comprises of mathematical formulating an optimal interval problem based on Multi-Attribute Utility Theory (MAUT). The aim of the proposed research is to develop a methodology with supporting tools for determination of optimal inspection in a maintenance planning to assure and preserve a desired level of performance measure such as reliability, availability, risk, etc. For verification and validation purposes, the proposed methodology (analysis approach) and tools (models) will be applied in a real case which given by the literature.

  • 17.
    Garmabaki, Amir
    et al.
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Ahmadi, Alireza
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Block, Jan
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Pham, Hoang
    Department of Industrial & Systems Engineering, Rutgers University, Piscataway, NJ.
    Kumar, Uday
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    A Reliability Decision Framework for Multiple Repairable Units2016Inngår i: Reliability Engineering & System Safety, ISSN 0951-8320, E-ISSN 1879-0836, Vol. 150, s. 78-88Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    In practice, the analyst is often dealing with multiple repairable units, installed in different positions or functioning under different operating conditions, and maintained by different disciplines. This paper presents a decision framework to identify an appropriate reliability model for massive multiple repairable units. It splits non-homogeneous failure data into homogeneous groups and classifies them based on their failure trends using statistical tests. The framework discusses different scenarios for analysing multiple repairable units, according to trend, intensity, and dependency of the units’ failure data. The proposed framework has been verified in a fleet of aircraft and in two simulated data sets. The results show a reliability model of multiple repairable units may contain a mixture of different stochastic models. Considering single reliability models for such populations may cause erroneous calculation of the time to failure of a particular unit, which can, in turn, lead to faulty conclusions and decisions. When dealing with massive and non-homogeneous multiple repairable units, the application of the proposed framework can facilitate the selection of an appropriate reliability model.

  • 18.
    Garmabaki, Amir
    et al.
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Ahmadi, Alireza
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Mahdavi, Iraj
    Mazandaran University of Science and Technology, Babol.
    Ahmadi, Mahdieh
    Mazandaran University of Science and Technology, Babol.
    Reliability modeling of open source software based on adoption behavior under stochastic environment2015Inngår i: Safety and reliability of complex engineered systems: proceedings of the 25th European Safety and Reliability Conference, ESREL 2015, Zürich, Switzerland, 7-10 September 2015 / [ed] Luca Podofilini; Bruno Sudret; Božidar Stojadinović; Enrico Zio; Wolfgang Kröger, Boca Raton: CRC Press, 2015, s. 3995-3999Konferansepaper (Fagfellevurdert)
    Abstract [en]

    In the current digitalized world, Open Source Software (OSS) methodology provides greater value to users and leads to increased revenue for the OSS companies. This paper investigates reliability modeling for OSS. Most of software reliability models proposed in literature for OSS projects are based on closed-form methodology and do not consider the properties of OSS in the model structure. This paper models the rate of adoption of volunteers to OSS using diffusion theory and considered as fault detection rate. However, the fault detection rate may vary in such a testing environment; a modified SRGM based on Itô type Stochastic Differential Equation (SDE) is proposed to describe realistic situations. The proposed model have been verified on real data sets from open source projects, as the Apache project, which has been released in the market with new features. Results show the proposed model can describe the failure process for open source software accurately.

  • 19.
    Garmabaki, Amir
    et al.
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Ahmadi, Alireza
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Mahmood, Yasser Ahmed
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Barabadi, Abbas
    Tromsø University.
    Reliability Modelling of Multiple Repairable Units2016Inngår i: Quality and Reliability Engineering International, ISSN 0748-8017, E-ISSN 1099-1638, Vol. 32, nr 7, s. 2329-2343Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    This paper proposes a model selection framework for analysing the failure data of multiple repairable units when they are working in different operational and environmental conditions. The paper provides an approach for splitting the non-homogeneous failure data set into homogeneous groups, based on their failure patterns and statistical trend tests. In addition, when the population includes units with an inadequate amount of failure data, the analysts tend to exclude those units from the analysis. A procedure is presented for modelling the reliability of a multiple repairable units under the influence of such a group to prevent parameter estimation error. We illustrate the implementation of the proposed model by applying it on 12 frequency converters in the Swedish railway system. The results of the case study show that the reliability model of multiple repairable units within a large fleet may consist of a mixture of different stochastic models, i.e. the HPP/RP, TRP, NHPP and BPP. Therefore, relying only on a single model to represent the behaviour of the whole fleet may not be valid and may lead to wrong parameter estimation.

  • 20.
    Garmabaki, Amir
    et al.
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Barabadi, Abbas
    Tromsø University.
    Fuqing, Yuan
    Tromsø University.
    Lu, J.
    University of Tromsø - The Arctic University of Norway.
    Ayele, Y.Z.
    University of Tromsø - The Arctic University of Norway.
    Reliability modeling of successive release of software using NHPP2015Inngår i: 2015 IEEE International Conference Industrial Engineering and Engineering Management (IEEM): Singapore, 6-9 Dec. 2015, Piscataway, NJ: IEEE Communications Society, 2015, s. 761-766, artikkel-id 7385750Konferansepaper (Fagfellevurdert)
    Abstract [en]

    This paper presents an effective reliability model for multi-release open source software (OSS), which derived based on software lifecycle development process (SDLC) proposed by Jørgensen [1]. Most of OSS reliability models do not consider the unique characteristic of OSS in the model. This model, combine bugs removed from pre-commit test and parallel debugging test phases. Furthermore, the proposed model is based on the assumptions that the total number of fault removal of the new release depends on the reported faults from the previous release and on the faults generated due to adding some new adds-on to the existing software system. The parameters of model have been estimated using three releases of the Apache project. In addition, three models in the literature are selected to compare with the proposed model. Comparison indicates that the proposed model is a suitable reliability model that fits the data across all the releases of the Apache project.

  • 21.
    Garmabaki, Amir
    et al.
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Birk, Wolfgang
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Signaler och system.
    Lindström, John
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Signaler och system.
    Software Fault Detection in Control Systems2017Inngår i: Risk, Reliability and Safety: Innovating Theory and Practice - Proceedings of the 26th European Safety and Reliability Conference, ESREL 2016 / [ed] Walls L.,Revie M.,Bedford T, CRC Press, 2017, s. 2006-2012Konferansepaper (Fagfellevurdert)
    Abstract [en]

    Fault detection in the software of control systems is a difficult task. In largely interconnected systems, not only the individual performance of one channel, but also its interaction with other components, must be considered. In this conceptual paper, we outline a new maintenance concept for the detection of software faults in control systems. The concept includes two approaches, morning gymnastics test and envelope analysis. The morning gymnastics test generates data for a baseline of the current operational abilities in contrast to the specified abilities and should be applied when feasible in continuous production systems. The test integrates historical and new sets of data to track degradation trends. Envelope analysis can be performed to detect operational anomalies and is based on subsequent deep analysis to distinguish software and hardware faults from each other. By using the envelope analysis it is possible to identify failures and disturbances affecting the control system. Thus, the proposed maintenance concept may facilitate detection and identification of potential failures in critical automated system.

  • 22.
    Garmabaki, Amir
    et al.
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Seneviratne, Dammika
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Ahmadi, Mahdieh
    Barabadi, Abbas
    Tromsø University.
    Kumar, Uday
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Data driven RUL estimation of rolling stock using intelligent functional test2017Inngår i: Risk, Reliability and Safety: Innovating Theory and Practice - Proceedings of the 26th European Safety and Reliability Conference, ESREL 2016 / [ed] Walls L.,Revie M.,Bedford T, London: CRC Press, 2017, s. 1994-1999Konferansepaper (Fagfellevurdert)
    Abstract [en]

    The rolling stock health condition is important for both passenger and freight trains in terms of safety, availability, punctuality and efficiency. Various inspection and maintenance methodologies are per-formed on rolling stock equipment to fulfill the above performance measures. This paper suggests a new approach, namely, intelligent functional test (IFTest) to estimate the remaining useful life (RUL) of the equipment, sub-systems and systems of rolling stock dynamically by data driven methods. IFTest generates a baseline of the current operational abilities in contrast to the required abilities. The test integrates the historical and new set of data to track the trend of degradation of equipment. With this approach, the operation and maintenance personnel have ample time to make decisions for the maintenance and failure consequences. In addition, it is supposed that by using such data we are achieving a more accurate result for the estimation of reliability and RUL of critical rolling stock equipment.

  • 23. Garmabaki, Amir Soleimani
    Some Contributions to Multi-Release Problems in Software Reliability and Successive Generations of Technologies2012Doktoravhandling, med artikler (Annet vitenskapelig)
    Abstract [en]

    Software reliability is defined as the probability of failure-free software operation for a specified period of time in a specified environment. The software reliability model is the tool, which can be used to evaluate software quantitatively, develop test status, schedule status and monitor the changes in reliability performance. In particular, software reliability models that describe the fault detection phenomenon in the testing phase are called software reliability growth models (SRGM). These models are useful in assessing reliability for the quality control and testing process control of software development. Software technologies like all systems have a hierarchy. Any software developed for a major application undergoes several generations of change. The changes improve the software and extend its useful life. In the last few decades it has been observed that the world of software development management (i.e. new product development, technology alliance etc.) has evolved rapidly due to the intensified market competition. Software companies plan successive releases of software by adding new features or new functionalities or try to improve performance of system as compared to previous releases. Microsoft Windows and Office, Adobe, Matlab represent good examples of such practice. This strategy provides some benefit for software companies. Few of them may be listed as: • It delivers quicker return to investment, limits the impact of market uncertainty, • Reduces the risk of project failure,• Provides firms with opportunities to refine their development methodologies • Improve product quality in later development cycles.The study in the thesis discusses various aspects of multi up-gradation SRGMs and successive generations of technologies. We have proposed mathematical models to manage the testing processes for building reliable software and predicting the adoption process of new technology products.As the software firm introduces new add-ons or features, software experiences a drastic increase in failure rate. Due to functionalities enhancements and feature up-gradations, the complexity of software is likely to be increased. We assume that, when the testing of a newly developed code is in progress there are chances that some faults of the previously released software may be detected and removed. In the thesis several aspects of multi release SRGM such as fault of different severity, imperfect debugging, effect of reported bugs are discussed. We have incorporated the concept of change in nature of fault during successive release of software.In addition, in some cases, fault is not corrected immediately once a failure is detected. For each detected fault, it is reported, diagnosed, verified, and then corrected. The time between detection and correction is not neligible in practical software testing process. The time to remove a detected fault depends on the complexity of the fault, the skill and experience of the debugging team, the available manpower, the software development environment. The unified framework for fault detection and correction processes for successive release of software is proposed.We have discussed two-dimensional modeling technique in area of software reliability engineering. In order to assure software quality and assess software reliability, many SRGMs have been proposed. In One-Dimension SRGMs researcher used one factor such as Testing-Time, Testing-Effort or Coverage, etc for designing the model but in two-Dimensional software reliability growth model, process depends on two-types of reliability growth factors like: ‘Testing-Time and Testing-Effort’ or ‘Testing-Time and Testing-Coverage’ or any combination between factors. The two dimensional models are developed using Cobb-Douglas production function. We have considered the case when failure distribution gets affected by factors, such as the running environment, testing strategy and resource allocation. Once these factors are changed during testing phase, it could result in failure intensity function that increases or decreases non-monotonically and the time point corresponding to abrupt fluctuations is called change point. The unified framework for two-dimensional SRGM with change-point for software reliability assessment is developed.Further, we have discussed a two-dimensional multi release SRGM by considering the combined effect of bugs encountered during testing of present release and user reported bugs from operational phase. A software cost model has been developed for multi up-gradation software reliability model under two-dimensional environments. Study of technology-market structure analysis involves describing how product generations compete against each other. New innovation in the market doesn’t immediately replace the previous one that it intends to substitute, but starts to compete with it. This creates a sequence of parallel diffusions of the existing generational products in the market. The need for introduction of a new technology generation can be explained with the help of S-curve or sigmoid diffusion curve. The extension of the Bass diffusion model that separates substitution from switching as well as leapfrogging The effect of Multi generation on Number of System-in-Use of the products has been formulated with the help of mathematical model in this thesis . The proposed methodology is built upon the assumption that adopters of each successive generation consist of four categories of customers, namely, (i) potential adoption of each generation,(ii) substitution, (iii) switchers, (iv) leapfrogging. In addition, The introduction time of a new product to the market is discussed. The timing decision depends on whether companies invest more time for product design or push the product to market before maturity. The study identifies attributes such as Customer’s Adoption Indicator and Cost that affect the introduction time of new generation. To trade-off between two decision factors, multi-attribute utility theory (MAUT) is applied in our decision space. Finally, we propose a modeling framework which accounts for the interactions between different dimensions of adoption i.e. time and price. Incorporating the dynamics of continuation time and the price of the product in the market has allowed us to model the diffusion process in two-dimensional framework. The applicability of the models proposed in the thesis is shown by validating them on software failure data sets obtained from different real software development projects using statistical package for social sciences (SPSS) and SAS software tool. The comparison with established models in terms of goodness of fit criteria, e.g.: Mean Squared Error (MSE), Coefficient of multiple determination (R2), Prediction Error (PE), Bias, Variation and Root Mean Squared Prediction Error (RMSPE) has been presented. Conclusion of the work done, directions for future research and an elaborate list of references are presented at the end of the thesis.

  • 24. Garmabaki, Amir Soleimani
    et al.
    Aggarwal, Anu G.
    Kapur, P.K
    Multi up-gradation software reliability growth model,with faults of different severity2011Inngår i: IEEE International Conference on Industrial Engineering and Engineering Management (IEEM), Singapore, 2011, s. 1539-1543Konferansepaper (Fagfellevurdert)
    Abstract [en]

    In today's environment of global competition where each company is trying to prove itself better than its competitors, software company have to continually do up-gradation or add-ons in their software to survive in the market. Each succeeding up-gradation offers some innovative performance enhancement or some new functionality etc distinguishing itself from the past release. But at the same time the amount of risk involved in up-gradation/add-ons of software with regard to introducing new faults or increasing the fault number in the software is also formidable. This model categorizes faults in two types: Type-1 and Type-2 (simple fault, hard fault namely) with respect to time which they take for isolation and removal after their observation. In this paper, we propose new model and new concept of multi release software development environment. The model developed is validated on real data sets for software which has been released in the market with new features.

  • 25. Garmabaki, Amir Soleimani
    et al.
    Aggrawal, anu G.
    Delhi University.
    Kapur, P.K
    Amity University.
    Yadavali, V.S.S
    Department of Industrial and System Engineering, University of Pretoria.
    Modeling two-dimensional software multi-upgradation and related release problem: a multi attribute utility approach2012Inngår i: International Journal of Reliability, Quality and Safety Engineering (IJRQSE), ISSN 0218-5393, Vol. 19, nr 3, artikkel-id 1250012-1Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    The today's fast-paced, competitive environment in the field of Science and Technology, demands highly reliable hardware and software in order to achieve new breakthroughs in quality and productivity. In this scenario, first release of software products includes enough features and functionality to make it useful for the customers. Later, software companies have to come up with upgradation or add-ons in their software to survive in the market through a series of releases. Each succeeding upgradation offers some innovative performance or new functionality, distinguishing itself from the past releases. In one-dimensional Software Reliability Growth Models (SRGM) researcher used one factor such as Testing-Time, Testing-Effort or Coverage, etc. but within a two-dimensional SRGM environment, the process depends on two-types of reliability growth factors like Testing-time and Testing-effort. In addition, we also consider the combined effect of bugs encountered during testing of present release and user reported bugs from the operational phase. The model developed in the paper takes into consideration the testing and the operational phase where fault removal phenomenon follows, logistic and Weibull model, respectively. The paper also comprises of formulating an optimal release problem based on Multi-Attribute Utility Theory (MAUT). Lastly, the model validation is done on real dataset of software already released in the market with successive generations.

  • 26.
    Garmabaki, Amir Soleimani
    et al.
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Ahmadi, Alireza
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Block, Jan
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Fleet-level reliability estimation of repairable units2015Inngår i: Safety and Reliability: Methodology and Applications / [ed] Tomasz Nowakowski; Marek Mlynczak; Anna Jodejko-Pietruczuk; Sylwia Werbinska-Wojciechowska, London: CRC Press, 2015, s. 1977-1982Konferansepaper (Fagfellevurdert)
    Abstract [en]

    This paper investigates reliability analysis of a repairable unit at fleet level. In fleet, multiple similar systems are running in different operating environments. In fact, due to the highly censored data as well as high variations in failure rate within the fleet, merging the datasets becomes a challenge. The non-parametric analysis is used to capture the failure trend of repairable units at fleet level. Consequently, fleet data have been aggregated and the actual number of failure has been compared with the expected total number of failures. In addition, parametric models are used to model the reliability trend obtained through a non-parametric approach to identify the reliability parameters at fleet level. Real data are used to demonstrate the applicability and validity of the proposed method. Results shows the accuracy of log-linear process is reasonably acceptable.

  • 27.
    Garmabaki, Amir Soleimani
    et al.
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Ahmadi, Alireza
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Kapur, P.K
    Amity University.
    Kumar, Uday
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Predicting software reliability in a fuzzy field environment2013Inngår i: International Journal of Reliability, Quality and Safety Engineering (IJRQSE), ISSN 0218-5393, Vol. 20, nr 3Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    The testing-development phase has been carried out in a given control environment. However, the product will be used in different operating environment by different end-users, which is unknown to the developer. The operating environment may range from a very clean one up to a harsh environment. These uncertain operating environments will impact to the reliability and performance of the software which may differ from the testing phase reliability. We consider that the effect of environment on reliability has a fuzzy nature. The fuzzy effects of the field environments can be captured by a unit-free environmental factor. To overcome this problem, the fuzzy probabilistic theory may be used in the processing of stochastic parameters, taking into account their fuzzy nature. The proposed model is based on Weibull distribution. The aim of this paper is to introduce a fuzzy field environment (FFE) reliability model that covers both the testing and operating phases in the development cycle. Illustration examples of the proposed model have been validated on data collected from two industries. © 2013 World Scientific Publishing Company.

  • 28.
    Garmabaki, Amir Soleimani
    et al.
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Ahmadi, Alireza
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Kapur, P.K
    Amity University.
    Kumar, Uday
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Predicting software reliability in a fuzzy-random field environment2012Konferansepaper (Fagfellevurdert)
    Abstract [en]

    The development of a new complex software or industrial system produces a series of prototypes that may contain faults during the processes, including development, design, and production. Therefore, during the early stages of prototyping complex systems, reliability often faces a major challenge in meeting the desired requirements level. For these reasons, a typical reliability improvement process is carried out in order to achieve a specific software/system reliability level. Incorrect estimation of reliability could lead to an inappropriate system design and implementation of incorrect maintenance policies.Many software reliability models have been proposed to help software developers and managers to assess the level of the reliability and estimation of the development cost. Among these software reliability models, Non-Homogenous Poisson Process (NHPP) based models have been successfully applied to model the software failure processes, and predict the number of software failures. NHPP has been used also to determine “time to stop testing” and release the software.Usually, the testing-development phase has been carried out in a given control environment. However, the product will be used in different operating environment by different end-users, which is unknown to the developer. The operating environment may range from a very clean one up to a harsh environment. These uncertain operating environments will impact to the reliability and performance of the software which may differ from the testing phase reliability. Hence the effect of environmental factors on reliability should be considered for estimation of the operational phase reliability. In fact the effect of environment on reliability has a fuzzy nature and quiet random. On the other hand, it is well known that the probability distribution and its parameters cannot be univocally defined. To overcome this problem, the fuzzy probabilistic theory may be used in the processing of stochastic parameters, taking into account their fuzzy nature. In fact, the fuzzy random effects of the field environments can be captured by a unit-free environmental factor. Based on the fuzzy probability distribution and its properties, we can define a fuzzy reliability function. The aim of this paper is to introduce a Fuzzy random field environment (FRFE) reliability model that covers both the testing and operating phases in the development cycle. The proposed model is based on Weibull distribution. It should be noted that the testing costs is one the major concern in software/system development. Several researcher investigated software/System release policies to minimize development cost while satisfying a reliability objective. Although the length of testing phase directly relates to the number of errors removed, but leads to a significant financial loss by increasing testing cost and delay in delivery. Further, releasing software in the market before reaching its desired level of reliability (which is fixed by the manager) may increase the maintenance cost during operational phase as well as create risk to lose future market.For a critical software system, the penalty costs resulting from the software failures are much more significant than the software development costs themselves. Therefore, the total software/ system cost should consist of not only the development costs, but also the penalty costs resulting from the software failure in operational phase. For software developers and managers, the following questions need to be answered (1) How to allocate the resources to ensure the on-time delivery of a software product? (2) When to stop testing and release the software from current software testing activities? (3) Is the software product really reliable in field? To answer the above mentioned questions, the paper proposes a cost function using proposed FRFE reliability model, to determine the optimal release policies.

  • 29.
    Garmabaki, Amir Soleimani
    et al.
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Kapur, P.K
    Aggarwal, Anu. G
    Yadavali, V.S.S
    The Impact of Bugs Reported from Operational Phase on Successive Software Releases2014Inngår i: International Journal of Productivity and Quality Management, ISSN 1746-6474, E-ISSN 1746-6482, Vol. 14, nr 4, s. 423-440Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Software testing is a necessary part of software development life cycle (SDLC) to achieve a high reliable software system. In today’s software environment of global competition where each company is trying to prove itself better than its competitors, software companies have to continually do up-gradation or add-ons in their software to survive in the market. Each succeeding up-gradation offers some innovative performance or new functionality, distinguishing itself from the past release. We consider the combined effect of bugs encountered during testing of present release and user reported bug from operational phase. The model developed in the paper takes into consideration the testing and the operational phase where fault removal phenomenon follows Kapur-Garg model and Weibull-model respectively. The model developed is validated on real datasets for software which has been released in the market with new features

  • 30. Garmabaki, Amir Soleimani
    et al.
    Kapur, P.K.
    Jyotish, N.P. Singh
    Ragini, K. Sanger
    The Optimal Time of New Generation Product in the Market2012Inngår i: Communications in Dependability and Quality Management, ISSN 1450-7196, Vol. 15, nr 1, s. 123-137Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Most product development activities are aimed at improving existing products by successive generation policy. The launch of a new product is a phase of development that commands a large commitment of time, money, and managerial resources. Determination of optimal introduction time is especially critical for high-technology products, where the introduction of each successive generation of a product requires the firm to explicitly consider its impact on the demand for preceding generations. Each generation has unique expectations, experiences, generational history, lifestyles, values, and demographics that influence behavior of potential buyers. Accordingly, many companies are reaching out to multi-generational consumers and trying to understand and gain the attention of these diverse buyers. The timing decision depends on whether companies invest more time for product design or push the product to market before maturity. The study identifies attributes such as Customer's Adoption Indicator and Cost that affect the introduction time of new generation. To trade-off between two decision factors, multi-attribute utility theory (MAUT) is applied in our decision space. We examine the case where a firm introduces successive generations of a durable product for which demand is characterized by an innovation diffusion process. Empirical implications of the proposed model have been validated on data collected from two industries (Semiconductor Industry DRAM shipments and IBM Mainframe Industry (USA)).

  • 31. Garmabaki, Amir Soleimani
    et al.
    Mashinchi, Mashaallah
    Garmabaki, Amir. H S.
    Application of fuzzy fixed point to optimization2009Konferansepaper (Fagfellevurdert)
  • 32.
    Garmabaki, Amir Soleimani
    et al.
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Marklund, Stefan
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Arkitektur och vatten.
    Thaduri, Adithya
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Hedström, Annelie
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Arkitektur och vatten.
    Kumar, Uday
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Underground pipelines and railway infrastructure: failure consequences and restrictions2019Inngår i: Structure and Infrastructure Engineering, ISSN 1573-2479, E-ISSN 1744-8980Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Underground pipelines are an essential part of the transportation infrastructure. The structural deterioration of pipelines crossing railways and their subsequent failures can entail critical consequences for society and industry, resulting in direct and indirect costs for all the stakeholders involved. Therefore, continuous and accurate condition assessment is critical for the effective management and maintenance of pipeline networks within the transportation infrastructure. The aim of this study has been to identify failure modes and consequences related to pipelines crossing railway corridors. Expert opinions have been collected through interviews and two sets of questionnaires have been distributed to the 291 municipalities in Sweden, with 137 responses in total. The failure analysis has revealed that pipe deformation has the highest impact, followed by pipe rupture at locations where pipelines cross railway infrastructure. For underground pipelines under railway infrastructure, ageing and the external load were awarded a higher ranking than other potential causes of pipeline failure.

    Authors gratefully acknowledge the funding provided by Sweden’sinnovation agency, Vinnova, through the strategic innovation programmeInfraSweden2030. The funding was granted in a competitiveapplication process that assessed replies to an open call for proposalsconcerning “Condition Assessment and Maintenance of TransportInfrastructure (Grant No. 2016-033113)”.

    Authors gratefully acknowledge the technical support and collaboration(In-kind support) of Arrsleff R€orteknik at Sweden, Luleå RailwayResearch Center (JVTC), Stormwater&Sewers and the SwedishTransport Administration (Trafikverket). In addition, the authors arethankful to the anonymous referees for their constructive commentsand Dr Matthias Asplund and Dr Masoud Naseri for their support andsuggestions.

  • 33.
    Garmabaki, Amir Soleimani
    et al.
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Thaduri, Adithya
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Hedström, Annelie
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Arkitektur och vatten.
    Kumar, Uday
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Laue, Jan
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Geoteknologi.
    Marklund, Stefan
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Arkitektur och vatten.
    Odelius, Johan
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Bansal, Tarun
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Geoteknologi.
    Rantatalo, Matti
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Asplund, Matthias
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Indahl, Stefan
    A Survey on Underground Pipelines and Railway Infrastructure at Cross-Sections2019Inngår i: ESREL-2019 / [ed] Michael beer, Enrico Zio, 2019Konferansepaper (Fagfellevurdert)
    Abstract [en]

    Underground pipelines are an essential part of the transportation infrastructure. The structural deterioration of pipelines crossing railways and their subsequent failures are critical for society and industry resulting in direct and indirect costs for all the related stakeholders. Pipeline failures are complex processes, which are affected by many factors, both static (e.g., pipe material, size, age, and soil type) and dynamic (e.g., traffic load, pressure zone changes, and environmental impacts). These failures have serious impacts on public due to safety, disruption of traffic, inconvenience to society, environmental impacts and shortage of resources. Therefore, continuous and accurate condition assessment is critical for the effective management and maintenance of pipeline networks within transportation infrastructure. The aim of this study is to identify failure modes and consequences related to the crossing of pipelines in railway corridors. Expert opinion have been collected through two set of questionnaires which have been distributed to the 291 municipalities in the whole Sweden. The failure analysis revealed that pipe deformation has higher impact followed by pipe rupture at cross-section with railway infrastructure. For underground pipeline under railway infrastructure, aging and external load gets higher ranks among different potential failure causes to the pipeline.

  • 34.
    Garmabaki, Amir
    et al.
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Thaduri, Adithya
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Seneviratne, Dammika
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Kumar, Uday
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Opportunistic inspection planning for Railway eMaintenance2016Inngår i: IFAC-PapersOnLine, ISSN 2405-8963, Vol. 49, nr 28, s. 197-202Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Railway infrastructure is a complex system that comprises of several subsystems which interacts in hierarchical, multi-distributive and multi-user environment. It is a difficult task to perform inspections for all the assets at an instant because the train management system decides when to conduct different types of inspection techniques on several assets in a particular track section. There are two main wastes of resources for inspection planning occurred in maintenance; under usage due to inaccurate prediction of failure and over usage because the necessary information already has been acquired from other sources. These irregularities lead to wastage of resources, for instance, human, machine and time that has tremendous implications on cost, availability and manpower. This paper proposes a methodology by using intelligent functional test outcome to assess the performability of an asset and integrating the data to the eMaintenance cloud platform of Swedish railway infrastructure. By implementing this methodology, we can achieve better planning of resources for optimal performance of assets. A case study is performed on Switches and Crossings of Swedish railway infrastructure for the applicability of the proposed methodology.

  • 35.
    Ghodrati, Behzad
    et al.
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Hoseinie, Hadi
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Garmabaki, Amir
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Reliability considerations in automated mining systems2015Inngår i: International Journal of Mining, Reclamation and Environment, ISSN 1748-0930, E-ISSN 1748-0949, Vol. 29, nr 5, s. 404-418Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Automation is the operation of machinery or processes by devices, such as robots and machines, able to make and execute decisions without human intervention. Automation is one of the most attractive research and development areas in mining, as it aims to solve many technical, production and safety problems in current and future mining. This paper studies the structure of automated mining systems from a reliability and failure occurrence perspective. It reviews the main subsystems and related failure modes. Based on field investigation and a literature review, it highlights some critical issues and technical difficulties. Finally, it presents some challenges for future automated mines and offers some related solutions

  • 36. Kapur, P.K
    et al.
    Aggarwal, Anu G.
    Garmabaki, Amir Soleimani
    Imperfect debugging software reliability growth model for multiple releases2011Inngår i: 4th National Conference on Computing for Nation Development-INDIACOM, New Delhi-India, 2011, s. 337-344Konferansepaper (Fagfellevurdert)
  • 37.
    Kapur, P.K
    et al.
    Amity University.
    Aggarwal, Anu G.
    Delhi University.
    Garmabaki, Amir Soleimani
    Singh, Gurinder
    Amity University.
    Modeling diffusion of successive generations of technology: A general framework2013Inngår i: International Journal of Operational Research, ISSN 1745-7645, E-ISSN 1745-7653, Vol. 16, nr 4, s. 465-484Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    In today's market where each company is trying to prove itself better than its competitors, companies have to continually bring new generations of their products so as to survive in the market. Each succeeding generation offers some innovative performance or new functionality, distinguishing itself from the past generation. Based on the behavioural assumptions of diffusion theory, this paper proposes an extension of the Bass diffusion model that separates substitution from switching as well as leapfrogging. We also present a relationship between our model and Norton-Bass model. Empirical implications of the proposed model have been validated on data collected from two industries (semiconductor industry dynamic random access memory shipments of six generations, mainframe industry (USA)). The model describes the growth of these generations quite effectively.

  • 38.
    Kapur, P.K.
    et al.
    Amity University, Department of Operational Research, University of Delhi.
    Aggarwal, Anu G.
    Delhi University.
    Garmabaki, Amir
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Tandon, Abhishek
    Multi-generational innovation diffusion modelling: a two dimensional approach2015Inngår i: International Journal of Applied Management Science, ISSN 1755-8913, E-ISSN 1755-8921, Vol. 7, nr 1, s. 1-18Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Majority of the consumer durables have multiple technological generations. High technology product comes in new generation where a new innovation offers a significant improvement in performance or benefits over the previous generation. New innovation in the market does not immediately replace the previous one that it intends to substitute, but starts to compete with it. This creates a sequence of parallel diffusions of the existing generational products in the market. In this paper, we develop a two-dimensional multigenerational innovation diffusion model which combines the adoption time of technological diffusion and price of the technology product. The proposed model helps in studying the marketing dynamics of the products which comes in generations. Technological adoptions and the role of the other dimensions are explicitly taken into consideration using Cobb-Douglas function. Empirical implications of the proposed model have been validated on data collected from DRAM (Semiconductor Industry DRAM shipments of six generations) in two plans.

  • 39. Kapur, P.K
    et al.
    Aggarwal, Anu GA.
    Garmabaki, Amir Soleimani
    Generalized framework for fault detection and correction processes for successive release of software2009Inngår i: 4th International Conference In Quality Reliability And Infocom Technology, Narosa Publications , 2009, s. 252-263Konferansepaper (Fagfellevurdert)
  • 40. Kapur, P.K
    et al.
    Garmabaki, Amir Soleimani
    Singh, J
    Software reliability multi up-gradation model with imperfect debugging2010Inngår i: International Congress on Productivity, Quality, Reliability, Optimization and Modeling, Allied Publishers Pvt. Ltd.: New Delhi, India , 2010, s. 136-149Konferansepaper (Fagfellevurdert)
  • 41. Kapur, P.K
    et al.
    Singh, Ompal
    Garmabaki, Amir Soleimani
    Singh, Jagvinder
    Multi up-gradation software reliability growth model with imperfect debugging.2010Inngår i: International Journal of Systems Assurance Engineering and Management, ISSN 0975-6809, E-ISSN 0976-4348, Vol. 1, nr 4, s. 299-306Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Due to demand of new features and highly reliable software system, the software industries are speeding their up-gradations/add-ons in the software. The life of software is very short in the environment of perfect competition. Therefore the software developers have to come up with successive up gradations to survive. The reported bugs from the existing software and Features added to the software at frequent time intervals lead to complexity in the software system and add to the number of faults in the software. The developer of the software can lose on market share if it neglects the reported bugs and up gradation in the software and on the other hand a software company can lose its name and goodwill in the market if the reported bugs and functionalities added to the software lead to an increase in the number of faults in the software. To capture the effect of faults due to existing software and generated in the software due to add-ons at various points in time, we develop a multi up-gradation, multi release software reliability model. This model uniquely identifies the faults left in the software when it is in operational phase during the testing of the new code i.e. developed while adding new features to the existing software. Due to complexity and incomplete understanding of the software, the testing team may not be able to remove/correct the fault perfectly on observation/detection of a failure and the original fault may remain resulting in the phenomenon known as imperfect debugging, or get replaced by another fault causing error generation The model developed is validated on real data sets with software which has been released in the market with new features four times.

  • 42.
    Mahmood, Yasser Ahmed
    et al.
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Garmabaki, Amir
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Ahmadi, Alireza
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Verma, Ajit Kumar
    Western Norway University of Applied Sciences.
    Reliability model for frequency converter in electrified railway2018Inngår i: International Journal of Electrical Power & Energy Systems, ISSN 0142-0615, E-ISSN 1879-3517, Vol. 94, s. 385-392Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Reliability analysis of frequency converters based on failures and outages reports constitute an important basis for asset performance and management. Two- and four-state reliability models that recognize the operating characteristics of base load units and peaking units are presented and compared in this study. In this study, a four-state model is modified to a three-state model by combining the ‘needed’ and ‘not-needed’ forced-out states. Moreover, the transitions in the three-state model for power frequency converter have been designed according to real operational data. An outage-reporting database modelled considering IEEE STD 762 is presented and compared with the existing failure-reporting database of the case considered here. Furthermore, a method to extract information missing in the failure-reporting database by electrical readings is proposed to meet the requirements of the outage-reporting database. The study found that the results of indexes based on the IEEE four-state model are not reasonable for the frequency converter given their differences with the gas-turbine results under operational conditions. The forced outage rates and availability factors of twelve actual traction frequency converters of Swedish railways network are presented to validate the modified model.

  • 43.
    Ramezani, Zahra
    et al.
    Department of Mathematics and Statistics, Mazandaran University, Babolsar.
    Pourdarvish, Ahmad
    Department of Mathematics and Statistics, Mazandaran University, Babolsar.
    Garmabaki, Amir
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Kapur, Parmad Kumar
    Amity Center for Interdisciplinary Research, Amity University.
    Optimal Reliability Equivalence Factor for Reliability System improvement Using Memetic Algorithm2017Inngår i: International Journal of Reliability, Quality and Safety Engineering (IJRQSE), ISSN 0218-5393, Vol. 24, nr 6, artikkel-id 1740008Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    In this paper, optimal reduction and redundancy methods for reliability system improvement have been proposed. Multilevel redundancy allocation problem (MLRAP) based on hot and cold redundancies have been considered. For various reasons, for instance, space limitation, high cost and so on, redundancy method cannot always be applied to improve system reliability. Hence the concept of equivalence has been presented to choice a more suitable method. In these conditions, optimal reduction method has been applied instead of optimal redundancy method. So that we decide what appropriate degree to decrease the failure rate is. To solve this problem, the value of optimal reliability equivalence factor is obtained by equating two obtained reliability functions based on optimal redundancy and reduction methods. Result shows that equivalence value maximizes the efficiency of the system performance in reduction method instead of redundancy method. Finally, the numerical examples illustrate the results obtained theoretically.

  • 44. Salarian, Hesam
    et al.
    Garmabaki, Amir Soleimani
    Zakariapour, M.
    Ghorbani, B.
    Study of heating effect of magnetic nanoparticles Hyperthermia with alternating magnetic field2011Inngår i: Int. Conf. on Advances in Mechanical Engineering, New Delhi, 2011, s. 11-15Konferansepaper (Fagfellevurdert)
  • 45.
    Singh, Ompal
    et al.
    Delhi University.
    Garmabaki, Amir Soleimani
    Kapur, P.K
    Unified framework for developing Two Dimensional software reliability growth models with change point2010Inngår i: IEEE International Conference on Quality And Reliability (ICQR), Bangkok, Thailand: IEEE Communications Society, 2010, s. 570-574Konferansepaper (Fagfellevurdert)
    Abstract [en]

    In order to assure software quality and assess software reliability, many software reliability growth models (SRGMs) have been proposed. In One-Dimension Software Reliability Growth Models researcher used one factor such as Testing-Time, Testing-Effort or Coverage, etc for designing the model but in Two-Dimensional software reliability growth model, process depends on two-types of reliability growth factors like: Testing-time and Testing-effort or Testing-time and Testing-Coverage or any combination between factors. Alsozin more realistic situations, the failure distribution can be affected by many factors, such as the running environment, testing strategy and resource allocation. Once these factors are changed during testing phase, it could result in failure intensity function that increases or decreases non-monotonically and the time point corresponding to abrupt fluctuations is called change point. In this paper, we discuss generalized framework for Two-Dimensional SRGM with change-point for software reliability assessment. The models developed have been validated on real data set.

  • 46.
    Soltanali, Hamzeh
    et al.
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik. Ferdowsi University of Mashhad, Mashhad, Iran.
    Garmabaki, Amir Soleimani
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Thaduri, Adithya
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Parida, Aditya
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Kumar, Uday
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Rohani, Abbas
    Ferdowsi University of Mashhad, Mashhad, Iran.
    Sustainable production process: An application of reliability, availability, and maintainability methodologies in automotive manufacturing2019Inngår i: Journal of Risk and Reliability, ISSN 1748-006X, E-ISSN 1748-0078, Vol. 233, nr 4, s. 682-697Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Automotive manufacturing industries are required to improve their productivity with higher production rates at the lowest cost, less number of unexpected shutdowns, and reliable operation. In order to achieve the above objectives, the application of reliability, availability, and maintainability methodologies can constitute for resilient operation, identifying the bottlenecks of manufacturing process and optimization of maintenance actions. In this article, we propose a framework for reliability, availability, and maintainability evaluation and maintenance optimization to improve the performance of conveying process of vehicle body in an automotive assembly line. The results of reliability, availability, and maintainability analysis showed that the reliability and maintainability of forklift and loading equipment are the main bottlenecks. To find the optimal maintenance intervals of each unit, a multi-attribute utility theory is applied for multi-criteria decision model considering reliability, availability, and costs. Due to the series configuration of conveying process in automotive assembly line, the optimized time intervals are obtained using opportunistic maintenance strategy. The results could be useful to improve operational performance and sustainability of the production process.

  • 47.
    Zaki, Rezgar
    et al.
    Department of Technology and Safety, UiT The Arctic University of Norway, Tromsø, Norway.
    Barabadi, Abbas
    Department of Technology and Safety, UiT The Arctic University of Norway, Tromsø, Norway.
    Qarahasanlou, Ali Nouri
    Faculty of Mining Engineering, Petroleum and Geophysics, Shahrood University of Technology, Shahrood, Iran.
    Garmabaki, Amir Soleimani
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    A mixture frailty model for maintainability analysis of mechanical components: a case study2019Inngår i: International Journal of Systems Assurance Engineering and Management, ISSN 0975-6809, E-ISSN 0976-4348Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Knowing the maintainability of a component or a system means that repair resource allocations, such as spare part procurement and maintenance training, can be planned and optimized more effectively. Repair data are often collected from multiple and distributed units in different operational conditions, which can introduce heterogeneity into the data. Part of such heterogeneity can be explained and isolated by the observable covariates, whose values and the way that they can affect the item’s maintainability are known. However, some factors which may affect maintainability are typically unknown (unobserved covariates), leading to unobserved heterogeneity. Nevertheless, many researchers have ignored the effect of observed and un-observed covariates, and this may lead to erroneous model selection, as well as wrong conclusions and decisions. Moreover, many authors have simplified their analysis by considering a complex system as a single item. In these studies, the assumption is that all repair data represent an identical repair process for the item. In practice, mechanical systems are composed of multiple parts, with various failure mechanisms, which need different repair processes (repair modes) to return to the operational phase; classical distribution, such as lognormal, which is only a function of time, may not be able to model such complexity. The paper utilizes the mixture frailty model (MFM) in the presence of some specific observed or unobserved covariates to predict maintainability more precisely. MFMs can model the effect of observed and unobserved covariates, as well as identifying different repair processes in the repair dataset. The application of the proposed model is demonstrated by a case study.

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